Predictive Accounting explores how accountants can use financial data, statistical modeling, and artificial intelligence to forecast future outcomes and guide strategic decision-making. It contrasts historical accounting with predictive methods, emphasizing tools like time series forecasting, machine learning, and scenario analysis. The book also covers practical applications such as predicting bad debts, detecting fraud, and improving budgeting through rolling forecasts and ERP integration. Additionally, it addresses the importance of data quality, ethical considerations, and effective communication of predictive insights to stakeholders.
